Diabetic Classification by Blood Vessel Analysis of Fundus Images

Diabetes may cause damage to the blood vessels of the retina which may eventually leads to blindness. Automatic segmentation of the retinal vasculature is a primary step towards automatic assessment of the retinal blood vessel features. This paper presents an automated method for the enhancement and segmentation of blood vessels in fundus images. The proposed system consists of three stages-first is preprocessing of retinal image to separate the green channel and second stage is retinal image enhancement and third stage is blood vessel segmentation using morphological operations and the features are extracted using the ttest algorithm. The proposed approach requires less segmentation time and achieves consistent vessel segmentation accuracy on normal images as well as images with pathology when compared to existing supervised segmentation methods.